Senior Data Scientist / AI Solutions Engineer

About the role

A global analytics team in Zurich is looking for a Senior Data Scientist / AI Solutions Engineer who combines advanced analytics, AI and engineering to solve complex commercial insurance challenges. The role develops scalable, data-driven products and intelligent automation that support underwriting excellence and portfolio performance across international markets. The position is full-time (80-100%), hybrid with up to two remote days per week.

Key responsibilities

• Partner with underwriting and business stakeholders on portfolio optimization, risk assessment, loss trend analysis and customer profitability, turning requirements into analytical frameworks and insights.
• Design, develop and deploy machine learning and AI models in production, including predictive modeling, NLP, classification, clustering, recommendation systems and anomaly detection, and continuously improve their performance, monitoring and governance.
• Build and maintain scalable data pipelines with cloud-native technologies, integrating structured and unstructured data and optimizing data processing workflows.
• Develop end-to-end analytical applications from proof-of-concept to enterprise deployment, working with product managers, engineers and business users.
• Mentor junior data scientists and engineers and promote best practices in analytics, AI, software development and data engineering.

Required profile

• Degree in Computer Science, Data Science, Statistics, Engineering, Mathematics or a related field.
• Several years of professional experience in Data Science, AI Engineering, Machine Learning or Data Engineering.
• Experience building and deploying production-ready analytical solutions.
• Fluent written and spoken English; German and English at C1-C2 level preferred.

Required skills

• Strong Python and SQL skills.
• Experience with large-scale data processing frameworks such as Spark or Databricks.
• Solid understanding of the machine learning lifecycle and software engineering best practices.
• Preferred: Azure, AWS or Google Cloud; MLOps, Docker and Kubernetes; NLP, LLMs or RAG; geospatial analytics; front-end and data visualization frameworks; insurance, reinsurance or risk management experience.

What we offer

• High-impact projects influencing global underwriting and portfolio strategy.
• A diverse team of analytics, engineering and insurance experts.
• Cutting-edge cloud, AI and data technologies.
• Opportunities for professional growth and career development.